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#include <Painter.h>
Classes | |
struct | PadCoordinates |
pad corner coordinates More... | |
Public Types | |
enum class | Type : int { Pad , Stack , FEC } |
Static Public Member Functions | |
static std::vector< PadCoordinates > | getPadCoordinatesSector () |
create a vector of pad corner coordinate for one full sector | |
static std::vector< PadCoordinates > | getStackCoordinatesSector () |
create a vector of stack corner coordinate for one full sector | |
static std::vector< PadCoordinates > | getFECCoordinatesSector () |
create a vector of FEC corner coordinates for one full sector | |
static std::vector< o2::tpc::painter::PadCoordinates > | getCoordinates (const Type type) |
static std::vector< double > | getRowBinningCM (uint32_t roc=72) |
static std::string | getROCTitle (const int rocNumber) |
ROC title from ROC number. | |
template<class T > | |
static TCanvas * | draw (const CalDet< T > &calDet, int nbins1D=300, float xMin1D=0, float xMax1D=0, TCanvas *outputCanvas=nullptr) |
template<class T > | |
static TCanvas * | draw (const CalArray< T > &calArray) |
template<class T > | |
static void | fillHistogram2D (TH2 &h2D, const CalDet< T > &calDet, Side side) |
template<class T > | |
static void | fillHistogram2D (TH2 &h2D, const CalArray< T > &calArray) |
template<class T > | |
static TH2 * | getHistogram2D (const CalDet< T > &calDet, Side side) |
template<class T > | |
static TH2 * | getHistogram2D (const CalArray< T > &calArray) |
static TH2Poly * | makeSectorHist (const std::string_view name="hSector", const std::string_view title="Sector;local #it{x} (cm);local #it{y} (cm)", const float xMin=83.65f, const float xMax=247.7f, const float yMin=-43.7f, const float yMax=43.7f, const Type type=Type::Pad) |
static TH2Poly * | makeSideHist (Side side, const Type type=Type::Pad) |
template<class T > | |
static void | fillPoly2D (TH2Poly &h2D, const CalDet< T > &calDet, Side side) |
template<class T > | |
static std::vector< TCanvas * > | makeSummaryCanvases (const CalDet< T > &calDet, int nbins1D=300, float xMin1D=0, float xMax1D=0, bool onlyFilled=true, std::vector< TCanvas * > *outputCanvases=nullptr) |
static std::vector< TCanvas * > | makeSummaryCanvases (const std::string_view fileName, const std::string_view calPadNames, int nbins1D=300, float xMin1D=0, float xMax1D=0, bool onlyFilled=true) |
static std::vector< TCanvas * > | makeSummaryCanvases (TTree &tree, const std::string_view draw, std::string_view cut="1", int nbins1D=300, float xMin1D=0, float xMax1D=0) |
static void | drawSectorsXY (Side side, int sectorLineColor=920, int sectorTextColor=1) |
draw sector boundaris, side name and sector numbers | |
static void | drawSectorLocalPadNumberPoly (short padTextColor=kBlack, float lineScalePS=1) |
static void | drawSectorInformationPoly (short regionLineColor=kRed, short rowTextColor=kRed) |
template<typename DataT > | |
static TH3F | convertCalDetToTH3 (const std::vector< CalDet< DataT > > &calDet, const bool norm=true, const int nRBins=150, const float rMin=83.5, const float rMax=254.5, const int nPhiBins=720, const float zMax=1) |
static std::vector< TCanvas * > | makeSummaryCanvases (const LtrCalibData <r, std::vector< TCanvas * > *outputCanvases=nullptr) |
make summary canvases for laser calibration data | |
static TCanvas * | makeJunkDetectionCanvas (const TObjArray *data, TCanvas *outputCanvas=nullptr) |
make a canvas for junk detection data | |
static void | adjustPalette (TH1 *h, float x2ndc, float tickLength=0.015) |
static TMultiGraph * | makeMultiGraph (TTree &tree, std::string_view varX, std::string_view varsY, std::string_view errVarsY="", std::string_view cut="", bool makeSparse=true) |
Static Public Attributes | |
static std::array< int, 6 > | colors |
static std::array< int, 10 > | markers |
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Adjust the X2 position and the tick length of the color axis
h | histogram to get z axis |
x2ndc | new x2 value of color axis in NDC |
tickLength | tick length of the color axis |
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convert std::vector<CalDet> objects (pad granularity) to a 3D-histogram with rxphixz binning. Each CalDet will be filled in a unique slice in the histogram
calDet | input objects which will be converted to a 3D histogram |
norm | whether to normalize the histogram (weighted mean) or to just integrate the values of the CalDet |
nRBins | number of bins in r direction of the output histogram |
rMin | min r value of the output histogram |
rMax | max r value of the output histogram |
nPhiBins | number of bins in phi direction of the output histogram |
zMax | z range of the output histogram (-zMax to zMax) |
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draw information of the sector: pad row in region, global pad row, lines for separating the regions
regionLineColor | color of the line which is drawn at the start of a sector |
rowTextColor | color of the text which is drawn |
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draw information of the sector: pad number in row
padTextColor | text color of pad number |
lineScalePS | setting the width of the lines of the pads which are drawn |
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draw sector boundaris, side name and sector numbers
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create a vector of FEC corner coordinates for one full sector
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create a vector of pad corner coordinate for one full sector
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binning vector with radial pad-row positions (in cm)
roc | roc number (0-35 IROC, 36-71 OROC, >=72 full sector) |
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create a vector of stack corner coordinate for one full sector
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make a canvas for junk detection data
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Make a multi graph with sparse option
Produce a multi graph from a tree, where varX
is a common x variable, e.g. a run number. TTree::Draw is used to fill the variables, so all expressions supported can be used. As in TTree::Draw, varsY have to be seperated by a ':'. For each variable a Graph will be created. Optionally one can give 'errVarsY', which must have the same number of entries as 'varsY'. In case the 'sparse' option is set (default), the x-axis will have as many bins as varX
has entries. The bins will be labelled accordingly. Colors and marker are assigned automatically using the ones defined in 'colors' and 'markers'
tree | the input tree to use |
varX | the x variable to create the sparse binning from |
varsY | the y variable for ech of which to create a graph, separated by ':' |
errVarsY | the y variable errors, separated by ':', same number of variables as in varsY required |
cuts | cut string to be used in the TTree::Draw |
makeSparse | make a sparse graph (default) |
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make a sector-wise histogram with correct pad corners
xMin | minimum x coordinate of the histogram |
xMax | maximum x coordinate of the histogram |
yMin | minimum y coordinate of the histogram |
yMax | maximum y coordinate of the histogram |
type | granularity of the histogram (per pad or per stack) |
make a side-wise histogram with correct pad corners
type | granularity of the histogram (per pad or per stack) |
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Create summary canvases for a CalDet object
1 Canvas with 2D and 1D distributions for each side 1 Canvas with 2D distributions for all ROCs 1 Canvas with 1D distributions for all ROCs
CalDet | object to draw |
nbins1D | number of bins used for the 1D projections |
xMin1D | minimum value for 1D distribution (xMin = 0 and xMax = 0 for auto scaling) |
xMax1D | maximum value for 1D distribution (xMin = 0 and xMax = 0 for auto scaling) |
outputCanvases | if outputCanvases are given, use them instead of creating new ones, 3 are required |
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make summary canvases for laser calibration data
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Create summary canvases for a CalDet object
1 Canvas with 2D and 1D distributions for each side 1 Canvas with 2D distributions for all ROCs 1 Canvas with 1D distributions for all ROCs
CalDet | object to draw |
nbins1D | number of bins used for the 1D projections |
xMin1D | minimum value for 1D distribution (xMin = 0 and xMax = 0 for auto scaling) |
xMax1D | maximum value for 1D distribution (xMin = 0 and xMax = 0 for auto scaling) |
fileName | input file name |
calPadNames | comma separated list of names of the CalPad objects as stored in the file. |
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Create summary canvases from pad calibration tree dumped via CalibTreeDump
1 Canvas with 2D and 1D distributions for each side 1 Canvas with 2D distributions for all ROCs 1 Canvas with 1D distributions for all ROCs
tree | input calibTree |
draw | draw string to use for the variable (1D) |
cut | cut string to use (default 1 = no cut) |
nbins1D | number of bins used for the 1D projections, if negative, exclude per ROC histograms |
xMin1D | minimum value for 1D distribution (xMin = 0 and xMax = 0 for auto scaling) |
xMax1D | maximum value for 1D distribution (xMin = 0 and xMax = 0 for auto scaling) |
Definition at line 631 of file Painter.cxx.